The lab utilizes a multitude of strategies to identify critical pathways required to promote tumorigenesis. These include high-throughput bioinformatics and structural modelling, siRNA screening, and precision genome editing to establish various functional genomic approaches to identify novel drivers. Utilizing bioinformatics we identify novel kinases enriched for functional mutations to hone in on activated enzymes that can serve as drug targets. We then assess the structural consequences of a subset of mutations in the respective kinases, where crystal structures are available, to determine if the mutations likely increase or decrease catalytic activity. These approaches have been successful in identifying kinases with activating mutations in lung cancer (ABL1 - Testoni et al EMBO Mol. Med. in press), as well as novel tumor suppressing kinases in colon and lung cancer that include MLK4 and DAPK3. In a second approach we use genetic dependency screens to identify mutationally activated drivers of lung cancer. Targeted genetic dependency screens are an effective way to uncover low frequency oncogenes that can serve as targets for therapeutic intervention for tumors of any origin. Specifically we identified FGFR4, PAK5, and MLK1 as kinases that harbour novel Gain of function (GOF) mutations in lung cancer patients and these mutations result in hyperactivation of the MEK/ERK pathway. The mutation frequency for the genes we identified ranged from 2-10% of lung cancers; given the frequency of lung cancer in the population, these targets could be exploited by pharmaceutical companies for drug discovery development. Going forward we are focused on novel drivers of the 3q amplicon that play a critical role in promoting tumorigenesis in lung squamous cell carcinoma, head and neck cancer, and ovarian cancer. These novel drivers can serve as targets of therapeutic intervention and an intense effort will focused on the mechanisms by which the novel kinases promote tumorigenesis. In addition, we are studying a novel kinase that represents a genetic dependency in KRAS mutant lung adenocarcinomas.